pokemon booster box canada Abyss Eye Booster Box (Japanese)
SKU: 94725275414
pokemon booster box canada

pokemon booster box canada Abyss Eye Booster Box (Japanese)

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Description

pokemon booster box canada Abyss Eye Booster Box (Japanese)Abyss Eye Booster Box (Japanese) The Abyss Eye booster box released in Japan on May 22, 2026, headlined by Mega Darkrai ex one of the most sought after sealed boxes of the year. This set sold out fast. Join the restock list below to get notified the moment it's back in stock. What's Inside the Abyss Eye Booster Box The Abyss Eye Booster Box contains 30 packs, with each pack containing 5 cards. The Abyss Eye set includes 81 main cards plus an extensive

Abyss Eye Booster Box (Japanese)

The Abyss Eye booster box released in Japan on May 22, 2026, headlined by Mega Darkrai ex — one of the most sought-after sealed boxes of the year. This set sold out fast. Join the restock list below to get notified the moment it's back in stock.

What's Inside the Abyss Eye Booster Box

The Abyss Eye Booster Box contains 30 packs, with each pack containing 5 cards. The Abyss Eye set includes 81 main cards plus an extensive lineup of Secret Rares (SAR and UR), making it smaller than traditional main sets and easier for collectors chasing a complete master set.

Mega Darkrai ex Headlines the Set

Officially revealed as the flagship of Abyss Eye, Mega Darkrai ex was introduced in December's Mega Dimension DLC and makes its TCG debut here. Its Pokedex entry reads: "Its dark power blocks out the sun, plunging the surrounding area into darkness. There is no escaping its evil eye."

Mega Darkrai's signature attack, also called Abyss Eye, instantly knocks out the opponent's Active Pokémon if it's affected by any Special Condition. Supporting cards include Chi-Yu, the Dark Bell trainer card, and a wave of Darkness-type Pokémon and trainer cards built around aggressive control.

The set is recognized for its intense "nightmare" themes and new Mega Evolution mechanics.

Where Abyss Eye Sits in the Mega Evolution Era

Abyss Eye is part of the Mega Evolution series and the first Japanese set to introduce the newer Mega Evolutions from the Mega Dimension DLC. Its English equivalent releases as the Pitch Black expansion on July 17, 2026; but the Japanese print runs first and historically holds stronger long-term collector value.

Abyss Eye Release Date and Shipping

  • Release date in Japan: May 22, 2026
  • Pre-order policy: orders placed now are not subject to additional charges if the price increases before release. Please refer to our Pre-Order Policy for more details.

If your order includes multiple pre-order items, they ship together after the latest release date.

Why Order from High Value Hobby

We ship from Canada with tracked, fully bubble-wrapped packaging and indestructo boxes, delivered in 5 business days or less across Canada and the US. Real collector support from Jazz, seven days a week. Send a DM on Instagram or email me at [email protected]

Sold out for now — join the restock list and we'll email you the moment Abyss Eye is back.

Looking for booster packs? Find Abyss Eye Booster Packs here.

Frequently Asked Questions

When did the Pokemon Abyss Eye booster box release?

The Abyss Eye booster box released in Japan on May 22, 2026. It sold out quickly — join our restock notification list to be alerted when inventory returns.

How many cards are in an Abyss Eye booster box?

Each Abyss Eye booster box contains 30 factory-sealed Japanese booster packs, with 5 cards per pack. The set itself has 81 main cards plus a strong lineup of Secret Rares including SAR and UR variants.

What is the flagship card in the Abyss Eye set?

The headliner is Mega Darkrai ex, introduced in December's Mega Dimension DLC. Its signature attack — also called Abyss Eye — instantly knocks out the opponent's Active Pokémon if it's affected by any Special Condition.

What is the English equivalent of the Abyss Eye set?

Abyss Eye's international equivalent is the Pitch Black expansion, releasing July 17, 2026. The Japanese version prints first and has historically held stronger long-term value among collectors and investors.

Is the Abyss Eye booster box factory sealed?

Yes. Every Abyss Eye booster box ships factory sealed straight from our vault, fully bubble-wrapped inside an indestructible shipping box.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
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Exchange/Return Notes
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SKU: 94725275414

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William P Ross
Bozeman, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
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Adam
Port Orchard, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026
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Amazon Customer
Port Orchard, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
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mackster
Omaha, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
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Stergios Papadimitriou
Grantham, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018

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